World's Best Scientists 2026 revealed!
Roberto Todeschini

Roberto Todeschini

D-Index & Metrics

Chemistry

D-Index
59
Citations
23659
World Ranking
9976
National Ranking
304

Roberto Todeschini publication distribution in Chemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Chemistry in 2026. The highlighted bar marks where Roberto Todeschini sits on this spectrum.

61–80 publications: 66 scientists 81–100 publications: 302 scientists 101–120 publications: 623 scientists 121–140 publications: 918 scientists 141–160 publications: 1,218 scientists 161–180 publications: 1,350 scientists 181–200 publications: 1,344 scientists 201–220 publications: 1,281 scientists 221–240 publications: 1,216 scientists 241–260 publications: 1,100 scientists 261–280 publications: 979 scientists 281–300 publications: 939 scientists 301–320 publications: 764 scientists 321–340 publications: 643 scientists 341–360 publications: 628 scientists 361–380 publications: 522 scientists 381–400 publications: 459 scientists 401–420 publications: 397 scientists 421–440 publications: 327 scientists 441–460 publications: 270 scientists 461–480 publications: 265 scientists 481–500 publications: 252 scientists 501–520 publications: 201 scientists 521–540 publications: 185 scientists 541–560 publications: 148 scientists 561–580 publications: 148 scientists 581–600 publications: 132 scientists 601–620 publications: 114 scientists 621–640 publications: 104 scientists 641–660 publications: 91 scientists 661–680 publications: 92 scientists 681–700 publications: 73 scientists 701–720 publications: 57 scientists 721–740 publications: 54 scientists 741–760 publications: 67 scientists 761–780 publications: 45 scientists 781–800 publications: 46 scientists 801–820 publications: 39 scientists 821–840 publications: 32 scientists 841–860 publications: 36 scientists 861–880 publications: 29 scientists 881–900 publications: 26 scientists 901–920 publications: 24 scientists 921–940 publications: 14 scientists 941–960 publications: 23 scientists 961–980 publications: 28 scientists 981–1,000 publications: 15 scientists 1,001–1,020 publications: 29 scientists 1,021–1,040 publications: 12 scientists 1,041–1,060 publications: 19 scientists 1,061–1,080 publications: 12 scientists 1,081–1,100 publications: 6 scientists 1,101–1,120 publications: 8 scientists 1,121–1,140 publications: 12 scientists 1,141–1,160 publications: 5 scientists 1,161–1,180 publications: 6 scientists 1,181–1,200 publications: 14 scientists 1,201–1,220 publications: 7 scientists 1,221–1,240 publications: 2 scientists 1,241–1,260 publications: 6 scientists 1,261–1,280 publications: 4 scientists 1,281–1,294 publications: 6 scientists 1,295+ publications: 100 scientists
61 publications 1,295+

This scientist: 246 publications — 48th percentile

48% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,295 publications or more.

Roberto Todeschini D-index placement in Chemistry in 2026

The chart shows the D-index (discipline H-index) distribution of Chemistry scientists ranked by Research.com in 2026. The highlighted bar marks where Roberto Todeschini sits on this spectrum.

40–41 D-Index: 289 scientists 42–43 D-Index: 612 scientists 44–45 D-Index: 808 scientists 46–47 D-Index: 776 scientists 48–49 D-Index: 835 scientists 50–51 D-Index: 861 scientists 52–53 D-Index: 872 scientists 54–55 D-Index: 933 scientists 56–57 D-Index: 1,051 scientists 58–59 D-Index: 930 scientists 60–61 D-Index: 882 scientists 62–63 D-Index: 834 scientists 64–65 D-Index: 731 scientists 66–67 D-Index: 775 scientists 68–69 D-Index: 683 scientists 70–71 D-Index: 646 scientists 72–73 D-Index: 561 scientists 74–75 D-Index: 501 scientists 76–77 D-Index: 437 scientists 78–79 D-Index: 388 scientists 80–81 D-Index: 354 scientists 82–83 D-Index: 292 scientists 84–85 D-Index: 275 scientists 86–87 D-Index: 254 scientists 88–89 D-Index: 235 scientists 90–91 D-Index: 185 scientists 92–93 D-Index: 192 scientists 94–95 D-Index: 155 scientists 96–97 D-Index: 163 scientists 98–99 D-Index: 125 scientists 100–101 D-Index: 105 scientists 102–103 D-Index: 105 scientists 104–105 D-Index: 112 scientists 106–107 D-Index: 88 scientists 108–109 D-Index: 68 scientists 110–111 D-Index: 69 scientists 112–113 D-Index: 65 scientists 114–115 D-Index: 79 scientists 116–117 D-Index: 61 scientists 118–119 D-Index: 44 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 40 scientists 124–125 D-Index: 33 scientists 126–127 D-Index: 26 scientists 128–129 D-Index: 34 scientists 130–131 D-Index: 35 scientists 132–133 D-Index: 25 scientists 134–135 D-Index: 27 scientists 136–137 D-Index: 17 scientists 138–139 D-Index: 16 scientists 140–141 D-Index: 20 scientists 142–143 D-Index: 20 scientists 144–145 D-Index: 15 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 9 scientists 150–151 D-Index: 16 scientists 152–153 D-Index: 11 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 3 scientists 158 D-Index: 3 scientists 159+ D-Index: 98 scientists
40 D-Index 159+

This scientist: 59 D-Index — 44th percentile

44% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 159 D-Index or more.

Best Publications

  • Handbook of Molecular Descriptors

    Roberto Todeschini;Viviana Consonni

  • QSAR Modeling: Where have you been? Where are you going to?

    Artem Cherkasov;Eugene N. Muratov;Eugene N. Muratov;Denis Fourches;Alexandre Varnek

  • Virtual computational chemistry laboratory - design and description

    Igor V. Tetko;Johann Gasteiger;Roberto Todeschini;Andrea Mauri

  • Molecular Descriptors for Chemoinformatics : Volume I : Alphabetical Listing / Volume II : Appendices, References

    Roberto Todeschini;Viviana Consonni

  • Molecular descriptors for chemoinformatics

    Roberto Todeschini;Viviana Consonni

  • Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information

    Iurii Sushko;Sergii Novotarskyi;Robert Körner;Anil Kumar Pandey

  • Comments on the Definition of the Q2 Parameter for QSAR Validation

    Viviana Consonni;Davide Ballabio;Roberto Todeschini

  • DRAGON SOFTWARE: AN EASY APPROACH TO MOLECULAR DESCRIPTOR CALCULATIONS

    Andrea Mauri;Viviana Consonni;Manuela Pavan;Roberto Todeschini

  • Comparison of different approaches to define the applicability domain of QSAR models.

    F Sahigara;K Mansouri;D Ballabio;A Mauri

  • Structure/Response Correlations and Similarity/Diversity Analysis by GETAWAY Descriptors. 1. Theory of the Novel 3D Molecular Descriptors

    Viviana Consonni;Roberto Todeschini;Manuela Pavan

  • Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection

    Igor V. Tetko;Iurii Sushko;Anil Kumar Pandey;Hao Zhu

  • New molecular descriptors for 2D and 3D structures. Theory

    Roberto Todeschini;Marina Lasagni;Emilio Marengo

  • CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    Kamel Mansouri;Ahmed Abdelaziz;Aleksandra Rybacka;Alessandra Roncaglioni

  • Structure/Response Correlations and Similarity/Diversity Analysis by GETAWAY Descriptors. 2. Application of the Novel 3D Molecular Descriptors to QSAR/QSPR Studies

    Viviana Consonni;Roberto Todeschini;Manuela Pavan;Paola Gramatica

  • Applicability domains for classification problems: Benchmarking of distance to models for Ames mutagenicity set.

    Iurii Sushko;Sergii Novotarskyi;Robert Körner;Anil Kumar Pandey

  • Quantitative structure-activity relationship models for ready biodegradability of chemicals.

    Kamel Mansouri;Tine Ringsted;Davide Ballabio;Roberto Todeschini

  • Similarity coefficients for binary chemoinformatics data: overview and extended comparison using simulated and real data sets.

    Roberto Todeschini;Viviana Consonni;Hua Xiang;John D. Holliday

  • New Local Vertex Invariants and Molecular Descriptors Based on Functions of the Vertex Degrees

    R Todeschini;Consonni

  • The K correlation index: theory development and its application in chemometrics

    R. Todeschini;V. Consonni;A. Maiocchi

  • Detecting bad regression models: multicriteria fitness functions in regression analysis

    Roberto Todeschini;Viviana Consonni;Andrea Mauri;Manuela Pavan

Frequent Co-Authors

Viviana Consonni
Viviana Consonni University of Milano-Bicocca
Davide Ballabio
Davide Ballabio University of Milano-Bicocca
Emilio Marengo
Emilio Marengo University of Eastern Piedmont Amadeo Avogadro
Igor V. Tetko
Igor V. Tetko Helmholtz Zentrum München
Denis Fourches
Denis Fourches North Carolina State University
Alexandre Varnek
Alexandre Varnek University of Strasbourg
Eugene N. Muratov
Eugene N. Muratov University of North Carolina at Chapel Hill
Johann Gasteiger
Johann Gasteiger University of Erlangen-Nuremberg
Dragos Horvath
Dragos Horvath University of Strasbourg
Alexander Tropsha
Alexander Tropsha University of North Carolina at Chapel Hill

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